Increasing energy efficiency with a smart farm—An economic evaluation

Pereira, Filipe; Caetano, Nídia S.; Felgueiras, Carlos

doi:10.1016/j.egyr.2022.01.074

Cited by 23 publications

(16 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Smart or modern agriculture requires more energy input than conventional agriculture due to high energy consumption in machinery and appliances [11]. The agriculture sector currently has huge innovations in technical and commercial resolutions that enhance the energy efficiency of farms which, therefore, point to cost reduction, especially in electricity bills [12]. According to a study in China regarding conventional agriculture [13], about 70% of energy are contributed by indirect energy use such as production of chemical fertilisers, pesticides, seeds, and others, while 30% of energy are from direct energy usage for land preparation, cultivation, and irrigation (on-site).…”

Section: Energy Management In Agriculturementioning

confidence: 99%

“…As suggested from [14], reducing the use of fossil fuels and fertilisers has a significant outcome on energy consumption. It is stated that about 83.2% decrease in energy consumption from the grid can be reached, equalling to 5,527 kg CO 2 savings, and eight years of return on investment (of RM170,528.24) [12]. Agriculture and energy grids have been facing substantial challenges, such as the deficiency of electricity supply to agricultural farms and the straits of renewable energy usage in the electricity sector [15].…”

Section: Energy Management In Agriculturementioning

confidence: 99%

See 1 more Smart Citation

A Review of Energy Management in Farm Automation: A Case of Paddy Plantation

Shafie,

Hami,

Hassan

et al. 2023

Advances in Economics, Business and Management Research

View full text Add to dashboard Cite

Farm automation is an innovative idea that specifically manages farms via the latest technologies such as drones, robotics, and artificial intelligences with the aim to raise the quality and quantity of crops, and at the same time, optimise the labour needed by production. In other words, these technologies that are related with "smart farming" assist to make the farms more effective and automate the crops' entire cycle. Through smart farming, main agricultural threats in the country can be diminished, the public is enticed to contribute towards the agriculture sector, the income level of local farmers will be increased, and most significantly, agricultural-based economic sectors will be transformed. Although this technology is fairly new, there is an increasing trend in the adoption of farm automation among traditional agriculture companies in Malaysia. This paper aims to review the pattern of energy management in farm automation, particularly focusing on paddy plantation. The adoption of automation and mechanisation should be further expanded to other segments of the paddy and rice supply chain. Through the review, we intend to provide better understanding related to farm energy consumption and implementation of best practices to optimise energy management on the farm, leading to better environmental performance as well great economic achievements of farmers.

show abstract

Section: Energy Management In Agriculturementioning

confidence: 99%

Section: Energy Management In Agriculturementioning

confidence: 99%

A Review of Energy Management in Farm Automation: A Case of Paddy Plantation

Shafie,

Hami,

Hassan

et al. 2023

Advances in Economics, Business and Management Research

View full text Add to dashboard Cite

show abstract

“…Excessive energy use has negative environmental consequences because most energy sources in farms have a high carbon footprint [69,70]. Moreover, the transition towards renewable energy (wind, solar and geothermal) in commercial farms was slow [71,72], and the alternative measures such as GPS guidance systems and auto-steering systems did not yield a significant reduction in machine time and fossil fuel consumption [70]. For example, a 5% reduction in fuel use translated to 1647-1866 L of fuel or US$734 and US$851 [70].…”

Section: Background On Bio-inspired Innovations In Agriculturementioning

confidence: 99%

Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering

Maraveas

Arvanitis

Bartzanas

et al. 2022

Arch Computat Methods Eng

View full text Add to dashboard Cite

The article reviewed the four major Bioinspired intelligent algorithms for agricultural applications, namely ecological, swarm-intelligence-based, ecology-based, and multi-objective algorithms. The key emphasis was placed on the variants of the swarm intelligence algorithms, namely the artificial bee colony (ABC), genetic algorithm, flower pollination algorithm (FPA), particle swarm, the ant colony, firefly algorithm, artificial fish swarm, and Krill herd algorithm because they had been widely employed in the agricultural sector. There was a broad consensus among scholars that certain BIAs' variants were more effective than others. For example, the Ant Colony Optimization Algorithm and genetic algorithm were best suited for farm machinery path optimization and pest detection, among other applications. On the contrary, the particle swarm algorithm was useful in determining the plant evapotranspiration rates, which predicted the water requirements and optimization of the irrigation process. Despite the promising applications, the adoption of hyper-heuristic algorithms in agriculture remained low. No universal algorithm could perform multiple functions in farms; different algorithms were designed to perform specific functions. Secondary concerns relate to data integrity and cyber security, considering the history of cyber-attacks on smart farms. Despite the concerns, the benefits associated with the BIAs outweighed the risks. On average, farmers can save 647–1866 L on fuel which is equivalent to US$734-851, with the use of GPS-guided systems. The accuracy of the BIAs mitigated the risk of errors in applying pesticides, fertilizers, irrigation, and crop monitoring for better yields.

show abstract

“…The design of energy management systems (EMSs) is a vast area of research with multiple applications in the contexts of microgrids, and active distribution networks, including applications in seaports [13,14], public buildings [15,16], hospitals [17], farms [18], and electrical distribution networks [11], among others. For this reason, in this research, we are interested in analyzing monopolar DC networks from the optimization point of view by proposing efficient energy management systems (EMS) for monopolar DC grids considering photovoltaic generation [19,20].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Dispatch of PV Plants in Monopolar DC Grids Using a Weighted-Based Iterative Convex Solution Methodology

2023

View full text Add to dashboard Cite

The design of an efficient energy management system (EMS) for monopolar DC networks with high penetration of photovoltaic generation plants is addressed in this research through a convex optimization point of view. The EMS is formulated as a multi-objective optimization problem that involves economic, technical, and environmental objective functions subject to typical constraints regarding power balance equilibrium, thermal conductor capabilities, generation source capacities, and voltage regulation constraints, among others, using a nonlinear programming (NLP) model. The main characteristic of this NLP formulation of the EMS for PV plants is that it is a nonconvex optimization problem owing to the product of variables in the power balance constraint. To ensure an effective solution to this NLP problem, a linear approximation of the power balance constraints using the McCormick equivalent for the product of two variables is proposed. In addition, to eliminate the error introduced by the linearization method, an iterative solution methodology (ISM) is proposed. To solve the multi-objective optimization problem, the weighted optimization method is implemented for each pair of objective functions in conflict, with the main advantage that in this extreme the Pareto front has the optimal global solution for the single-objective function optimization approach. Numerical results in the monopolar version of the IEEE 33-bus grid demonstrated that the proposed ISM reaches the optimal global solution for each one of the objective functions under analysis. It demonstrated that the convex optimization theory is more effective in the EMS design when compared with multiple combinatorial optimization methods.

show abstract

Increasing energy efficiency with a smart farm—An economic evaluation

Cited by 23 publications

References 13 publications

A Review of Energy Management in Farm Automation: A Case of Paddy Plantation

A Review of Energy Management in Farm Automation: A Case of Paddy Plantation

Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering

Multi-Objective Dispatch of PV Plants in Monopolar DC Grids Using a Weighted-Based Iterative Convex Solution Methodology

Contact Info

Product

Resources

About